The Data Scientist position is a hands-on role responsible for the end-to-end design, testing and development of analytics solutions for Service Operations. You will work closely with other team members and business stakeholders to apply machine learning, deep learning, NLP and other advanced analytics. You will research and prepare data for analysis, perform data exploration, apply machine learning and statistical techniques to draw conclusions and build innovative products to improve operational effectiveness and efficiency.

Responsibilities:

• Work individually and/or with team members to design and develop machine learning models (both supervised and unsupervised) for prototyping or ad-hoc analyses.
• Apply data mining techniques and perform statistical analysis as needed.
• Collect and organize information from a variety of data sources.
• Write queries to underlying Microsoft SQL Server and Oracle databases.
• Work with business partners to learn and understand the specific domain
• Clearly present findings to leadership and be able to articulately influence the Business Case for change.
• Interview stakeholders in order to understand pain points and formulate hypothesis for scenario modeling.

Qualifications:

• Expertise in data mining algorithms and statistical modeling techniques such as clustering, classification, regression, decision trees, neural nets, support vector machines, ensemble modeling and text mining techniques such as sentiment analysis, topic modeling and entity extraction.
• Exceptional quantitative skills and attention to detail.
• Multi-year experience with Python/R and SQL.
• Degree in Data Science, Computer Science, Statistics, Mathematics, Computational Linguistics or related field. MS or PhD preferred.
• Ability to establish and maintain strong working relationships across the organization.
• Experience with measuring the behaviors of customers navigating various Omni-Channel service platforms is a plus (i.e. Website visits, App usage, Call Center, voice-activated technology, etc).

The Data Scientist reports to the Director of Machine Learning and AI. The machine learning team is responsible for the invention, analysis, and deployment of new machine learning techniques using organisations data to improve business result.This is a unique opportunity for a passionate individual about innovation in machine learning, and AI. This is a fast-paced, collaborative and iterative environment requiring quick learning, agility and flexibility.

Responsibilities:

• Innovate, implement and test machine learning and deep learning techniques at scale.
• Analyze the quality and calibration of predictive models.
• Collaborate with machine learning and engineering team members for deployment of new machine learning techniques, and follow deployments tracking issues and successes.
• Interface with medical coders, administrators, and physicians to understand the strengths and weaknesses of existing products and to help develop new machine learning-empowered products.

Qualifications:

• M.S. in Computer Science, Mathematics, Statistics, or related field and 5 years of related work experience in ML and AI.
• Hands on experience with machine learning approaches and understanding of the analysis, testing processes of machine learning techniques.
• Familiarity with deep learning approaches such as CNN, RNN and Reinforcement learning.
• Hands on experience with SQL and non-SQL databases.
• Proficiency in one or more of programming languages such as Python, Java, C, or C++.
• Demonstrated end-to-end project leadership.
• Strong verbal, visual, and written communication skills.

Beneficial Experience:

• PhD in Computer Science, Mathematics or related field.
• Demonstrable experience with NLP applications.
• Publications in major ML/NLP conferences, and/or participation in Kaggle or similar competitions
• Some knowledge of US healthcare systems.

Job Description:

You will be part of a team building the next generation data warehouse platform and will design, develop, and maintain complex extract, transform, and load (ETL) data pipelines using large heterogeneous datasets. You will also build data engineering solutions for complex data models that express business processes. Your expertise with leading technologies and tools such as Oracle, Postgres, Python, etc. will result in a valuable modern data warehouse that supports critical business decisions and data analysis processes. Your collaboration and communication skills will help to establish stakeholder relationships and ensure that your work products are in alignment with project goals. Most importantly, you will be passionate about working with data and will be a significant contributor.

Responsibilities:

• Design, develop, and automate scalable data engineering solutions by leveraging cloud infrastructure. Extend or migrate existing data pipelines to new cloud environment.
• Lead technical projects involving design and development of data pipelines for complex datasets. Document project plans, outline tasks and milestones, provide estimation of effort.
• Work closely with business partners to devise and manage data pipelines, load frequency, data delivery mechanisms, and performance tuning.
• Identify and implement best practices for data engineering and software development to ensure quality delivery of enterprise solutions.
• Help enable team alignment by participating in code reviews, change management and team meetings.
• Develop and maintain detailed technical documentation of data engineering solutions.
• Collaborate with key stakeholders, both internal and external, including enterprise data architect, data modelers, and subject matter experts (SMEs).

Qualifications:

• Five or more years of professional experience as data engineer. Bachelor’s degree in Computer Science or equivalent experience.
• Demonstrated experience in data warehousing and ETL development.
• Experience building complex data pipelines using large, disparate data sources.
• Demonstrated expert knowledge in SQL.
• Demonstrated experience working with relational databases such as Oracle, Postgres and other modern database technologies.
• Proficiency in modern programming languages such as Python, R, Java.
• Thorough understanding of data movement and transformation tools, such as Informatica, Datastage or equivalent.
• Demonstrated experience in selecting tools, methods, techniques, and evaluation criteria for designing optimal data engineering solutions.
• Demonstrated experience in leading complex technical projects, including assigning tasks and selecting team members.
• Ability to make technical presentations to teams, focus groups, management, and governance committees.
• Excellent customer service, communication and collaboration skills.

Preferred Qualifications:

• Five years or more experience as data engineer designing and implementing complex data pipelines.
• Master’s degree in Computer Science, Information Technology or related field.
• Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.).
• Experience with AWS technologies.